October 31, 2024
CSCS Conference Room
Europe/Zurich timezone

Description

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Key Questions

  1. Challenges in Offering AI/ML Services:
    1. What are the unique challenges HPC centers face in providing AI/ML services alongside traditional HPC capabilities?
    2. How do we ensure scalability and efficiency in AI/ML workflows within HPC infrastructures?
  2. User Expectations:
    1. What are the expectations of users regarding AI/ML services within HPC environments?
    2. How can HPC centers tailor their offerings to meet these expectations effectively?
  3. Concrete Machine Learning Workflows:
    1. What are the typical workflows involved in integrating ML/AI with HPC resources?
    2. How can these workflows be optimized for performance and reliability?
  4. Tools for AI/ML Services:
    1. What tools and frameworks are currently available for providing AI/ML services in HPC settings?
    2. Are there any gaps in tooling that need to be addressed to better support AI/ML integration?
  5. Data Requirements and Considerations:
    1. What specific requirements does ML/AI integration impose on data storage, access, and management within HPC centers?
    2. How can HPC centers navigate the complexities of handling diverse data types and sources?

 

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Ends
Europe/Zurich
CSCS Conference Room
CSCS Via Trevano 131 6900 Lugano
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  • Maria Grazia Giuffreda
  • Pablo Fernandez
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